Generative AI Market Report by Offering Type (Image, Video, Speech, and Others), Technology Type (Autoencoders, Generative Adversarial Networks, and Others), Application (Healthcare, Generative Intelligence, Media and Entertainment, and Others) and Region 2024-2032

Generative AI Market Report by Offering Type (Image, Video, Speech, and Others), Technology Type (Autoencoders, Generative Adversarial Networks, and Others), Application (Healthcare, Generative Intelligence, Media and Entertainment, and Others) and Region 2024-2032

Report Format: PDF+Excel | Report ID: SR112024A6374
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Market Overview:

The global generative AI market size reached US$ 12.3 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 58.0 Billion by 2032, exhibiting a growth rate (CAGR) of 18.81% during 2024-2032. The increasing amount of generated data, the development of advanced machine learning techniques, expanding information technology (IT) sector and the rising product adoption across a wide range of industries are some of the major factors propelling the market.

Report Attribute
Key Statistics
Base Year
Forecast Years
Historical Years
Market Size in 2023
US$ 12.3 Billion
Market Forecast in 2032
US$ 58.0 Billion
Market Growth Rate (2024-2032)

Generative AI refers to a branch of artificial intelligence (AI) that focuses on generating new content, such as images, videos, music, or text. Unlike traditional AI models that are designed for classification or prediction tasks, generative AI models aim to create new content that is not explicitly present in the training data. They learn from large datasets and generate new examples by understanding patterns and relationships within the data. They can also generate content that resembles the training data, imitating the style, structure, and characteristics of the input data. As a result, it is widely employed across several industries, such as healthcare, IT, robotics, and BFSI.

Global Generative AI Market

The market is primarily driven by the expanding information technology (IT) sector and the increasing usage of AI-integrated systems for enhancing productivity and agility. Besides this, the emerging popularity of generative AI for assisting chatbots in conducting effective conversations and enhancing customer satisfaction is also contributing to market growth. Generative AI can create personalized recommendations, tailored advertisements, and customized products based on individual preferences and behavior. Moreover, the rising utilization of generative AI for creating virtual worlds in the metaverse and producing digital artworks using text-based descriptions and generating unique and innovative content is also propelling the market growth. Furthermore, the market has attracted significant investments and funding from both established companies and venture capitalists. This influx of capital has accelerated research, development, and commercialization efforts, further creating a favorable market outlook across the globe.

Generative AI Market Trends/Drivers:

An increasing amount of generated data

The proliferation of digital devices, social media, and the internet has resulted in an explosion of data. Generative AI algorithms require large amounts of data to learn and create new content. Moreover, more data allows generative AI models to capture a broader range of patterns and variations present in the real world. This can result in more realistic and accurate content generation. For example, in computer vision, a larger dataset of images can help generative AI models produce more visually convincing and detailed images. Besides, the increasing volume of generated data can be used for data augmentation and synthesis purposes. By combining real and generated data, generative AI models can be trained on augmented datasets to improve generalization and adaptability. This approach helps address challenges like limited real-world training data and enables generative AI models to handle a wider range of scenarios.

The Development of advanced machine learning techniques

These techniques have expanded the capabilities of generative AI models, leading to improved performance, increased efficiency, and the ability to generate more realistic and high-quality content. Deep learning, specifically deep neural networks, has revolutionized the field of generative AI with their multiple layers of interconnected nodes that can learn complex patterns and hierarchies in data. This has enabled generative AI models to capture intricate details and generate more nuanced content, such as high-resolution images or realistic speech. Moreover, transfer learning has facilitated the application of pre-trained models to generative AI tasks. As a result, the market is witnessing positive growth.

Rising applications in various industries

The versatility and potential of generative AI across different sectors have driven its adoption and contributed to market growth. Generative AI has found extensive use in the entertainment and media industries. It is used to create realistic computer-generated graphics and special effects in movies and video games. Moreover, generative AI has transformed advertising and marketing strategies by enabling personalized and customized content creation, allowing businesses to tailor their messaging and offers to individual consumers. Besides, it is used in the healthcare sector for tasks such as medical image analysis, drug discovery, disease diagnosis, and treatment planning. Generative AI models can generate synthetic medical images, simulate physiological systems, and assist in precision medicine initiatives.

Generative AI Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the global generative AI market report, along with forecasts at the global, regional, and country levels from 2024-2032. Our report has categorized the market based on offering type, technology, and application.

Breakup by Offering Type:

Market Breakup by Offering Type

  • Image
  • Video
  • Speech
  • Others

The report has provided a detailed breakup and analysis of the market based on the offering type. This includes image, video, speech, and others.

There is a significant consumer demand for high-quality and visually appealing images, which has driven the adoption of generative AI techniques for image generation. Moreover, generative AI techniques for image generation have made significant advancements in recent years. These techniques have become more sophisticated and capable of generating high-quality, realistic, and diverse images.

Video content consumption has also been on the rise across various platforms, including social media, streaming services, online advertising, and virtual communication. The growing demand for video content has escalated the adoption of generative AI to enhance and automate video creation processes.

The rise of voice assistants, such as Amazon Alexa, Google Assistant, and Apple Siri, has increased the demand for natural and human-like speech generation. Moreover, speech generation models can be employed in conversational agents and chatbots to generate human-like speech responses, thus accelerating the product adoption in this segment.

Breakup by Technology Type:

  • Autoencoders
  • Generative Adversarial Networks
  • Others

Generative adversarial networks hold the largest share

A detailed breakup and analysis of the market based on technology has also been provided in the report. This includes autoencoders, generative adversarial networks, and others. According to the report, generative adversarial networks accounted for the largest market share.

GANs have found applications in numerous domains and industries, making them highly versatile. They are applied in image synthesis, style transfer, image-to-image translation, video generation, text generation, data augmentation, and more. The ability of GANs to generate new, diverse, and realistic samples has made them a go-to choice for various generative tasks, driving their market share. Moreover, the availability of open-source implementations and pretrained GAN models has facilitated the adoption and usage of GANs. These resources, combined with easy-to-use libraries and frameworks like TensorFlow and PyTorch, have lowered the barrier to entry for developers and researchers, allowing them to leverage GANs for their applications without starting from scratch.

Autoencoders can generate new samples by sampling from the learned latent space. This makes autoencoders capable of generating new instances of data, making them suitable for applications such as image synthesis, text generation, and data augmentation, thus increasing their market share.

Breakup by Application:

Market Breakup by Application

  • Healthcare
  • Generative Intelligence
  • Media and Entertainment
  • Others

Media and entertainment represent the leading application segment

A detailed breakup and analysis of the market based on application has also been provided in the report. This includes healthcare, generative intelligence, media and entertainment, and others. According to the report, media and entertainment accounted for the largest market share.

The media and entertainment industry heavily relies on visual content, including movies, TV shows, video games, virtual reality (VR), and augmented reality (AR) experiences. Generative AI techniques, such as image and video generation, can play a crucial role in creating visually stunning and realistic content. These techniques enable the generation of computer-generated graphics, special effects, virtual environments, and characters, enhancing the overall visual experience for audiences. Moreover, animation studios and visual effects companies are increasingly leveraging generative AI techniques to streamline and enhance their production processes.

Moreover, generative AI techniques are used in the healthcare sector for X-rays, MRIs, and CT scans, to enhance image quality, assist in diagnosis, and aid in the detection of abnormalities or diseases. They can also generate high-resolution images, reconstruct missing data, and assist radiologists and clinicians in making accurate diagnoses. This can lead to improved patient care, early detection of diseases, and better treatment planning.

Breakup by Region:

Market Breakup by Region

  • North America
    • United States
    • Canada
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Others
  • Europe
    • Germany
    • France
    • United Kingdom
    • Italy
    • Spain
    • Russia
    • Others
  • Latin America
    • Brazil
    • Mexico
    • Others
  • Middle East and Africa

North America exhibits a clear dominance in the market, accounting for the largest generative AI market share

The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. 

North America has an active AI research community, with renowned institutions and researchers driving advancements in generative AI. Prominent research centers and universities in the region conduct cutting-edge research, publish influential papers, and contribute to the development of generative AI techniques. This research excellence translates into industry leadership and market dominance. Besides this, the region’s large population, high consumer spending, and advanced technology infrastructure create a favorable environment for the adoption and commercialization of generative AI solutions. Furthermore, North America has relatively supportive regulations and policies for AI and emerging technologies. Governments in the region have recognized the potential of AI and actively promote its development through investments, research grants, and initiatives.

Asia Pacific is expected to witness significant growth during the forecast period, due to rising digitization in various industries, increasing cloud networks and data centers, and expanding IT industry.

Competitive Landscape:

The generative AI landscape is rapidly evolving due to various developments by leading companies in the field. Nowadays, the leading market players are developing new models, refining existing ones, and introducing innovative techniques to enhance the quality and diversity of generated content. They are also investing in research and development efforts to improve image and video synthesis, enabling applications such as virtual reality, gaming, content creation, and special effects. Besides this, various key players are focused on making generative AI more accessible to a broader range of users. They are developing user-friendly tools, platforms, and APIs that enable developers, researchers, and businesses to leverage generative AI capabilities. Moreover, they are engaging in partnerships and mergers and acquisitions to strengthen their foothold in the market.

The report has provided a comprehensive analysis of the competitive landscape in the global generative AI market. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

  • Adobe Inc.
  • Amazon Web Services Inc.
  • D-ID
  • Google LLC
  • MOSTLY AI Inc.
  • OpenAI
  • Synthesia

Recent Developments:

  • OpenAI, has been actively involved in advancing generative AI. In 2021, they introduced their ChatGPT model, which allows users to engage in interactive and dynamic conversations.
  • Adobe Inc. has developed Adobe Sensei, which utilizes generative AI techniques to enhance image editing workflows, automate repetitive tasks, and assist in creative content generation.
  • Google LLC announced a partnership with OpenAI to provide access to OpenAI's advanced language models, including GPT-3, to Google Cloud customers. This collaboration aimed to make OpenAI's generative AI technologies more accessible and foster innovation in natural language processing applications.

Generative AI Market Report Scope:

Report Features Details
Base Year of the Analysis 2023
Historical Period 2018-2023
Forecast Period 2024-2032
Units US$ Billion
Scope of the Report Exploration of Historical and Forecast Trends, Industry Catalysts and Challenges, Segment-Wise Historical and Predictive Market Assessment:
  • Offering Type
  • Technology Type
  • Application
  • Region
Offering Types Covered Image, Video, Speech, Others
Technology Types Covered Autoencoder, Generative Adversarial Networks, Others
Applications Covered Healthcare, Generative Intelligence, Media and Entertainment, Others
Regions Covered  Asia Pacific, Europe, North America, Latin America, Middle East and Africa
Countries Covered United States, Canada, Germany, France, United Kingdom, Italy, Spain, Russia, China, Japan, India, South Korea, Australia, Indonesia, Brazil, Mexico
Companies Covered Adobe Inc., Amazon Web Services Inc., D-ID, Google LLC, MOSTLY AI Inc., OpenAI, and Synthesia
Customization Scope 10% Free Customization
Report Price and Purchase Option Single User License: US$ 2499
Five User License: US$ 3499
Corporate License: US$ 4499
Post-Sale Analyst Support 10-12 Weeks
Delivery Format PDF and Excel through Email (We can also provide the editable version of the report in PPT/Word format on special request)

Key Benefits for Stakeholders:

  • IMARC’s report offers a comprehensive quantitative analysis of various market segments, historical and current market trends, market forecasts, and dynamics of the generative AI market from 2018-2032.
  • The research study provides the latest information on the market drivers, challenges, and opportunities in the global generative AI market.
  • The study maps the leading, as well as the fastest-growing, regional markets. It further enables stakeholders to identify the key country-level markets within each region.
  • Porter's five forces analysis assist stakeholders in assessing the impact of new entrants, competitive rivalry, supplier power, buyer power, and the threat of substitution. It helps stakeholders to analyze the level of competition within the generative AI industry and its attractiveness.
  • Competitive landscape allows stakeholders to understand their competitive environment and provides an insight into the current positions of key players in the market.

Key Questions Answered in This Report

As per the IMARC Group, the size of global generative AI market was US$ 12.3 Billion in 2023. Factors such as the rising applications of technologies, such as super-resolutions, text-to-video conversion, and text-to-image conversion, and the rising demand to modernize the workflow across several industries will drive the demand for generative artificial intelligence applications, amongst several industries. The rising advancements in deep learning and machine learning and the rising use of artificial intelligence (AI)-generated content for marketed strategies will also drive the generative AI market growth. Also, the rising growth of the information technology (IT) sector and the propelling use of AI-integrated systems across various verticals to promote both productivity and agility will lead to an increase in the generative AI market growth.

We expect the global generative AI market to exhibit a CAGR of 18.81% during 2024-2032.

The rising adoption of generative AI across several industries, such as healthcare, Information Technology (IT), media and entertainment, etc., owing to its various benefits, including enhanced identity protection, better comprehension of abstract theories, the creation of high-quality content, decreased financial risks, etc., is primarily driving the global generative AI market.

The generative AI market can be deemed highly optimistic in the future. Factors that are attributed to the growth of generative AI comprise the rising evolution of artificial intelligence and deep learning and the increasing era of content creation and creative applications. The rising innovation of cloud storage, thereby enabling easier access to data will also lead to an increase in the demand for generative AI. The growing number of partnerships, collaborations, and product launches that are offering lucrative opportunities to the market players in this domain will also lead to a rise in the growth of the generative AI market. Furthermore, the increasing investments in Artificial Intelligence research and development across the globe will also cause an increase in the generative AI market growth.

The sudden outbreak of the COVID-19 pandemic has led to the growing deployment of generative AI by numerous organizations to create new digital videos, images, texts, audio, or code, during the remote working scenario.

Based on the technology type, the global generative AI market has been segregated into autoencoders, generative adversarial networks, and others. Among these, generative adversarial networks currently hold the largest market share.

Based on the application, the global generative AI market can be bifurcated into healthcare, generative intelligence, media and entertainment, and others. Currently, the media and entertainment sector exhibits a clear dominance in the market.

On a regional level, the market has been classified into North America, Asia-Pacific, Europe, Latin America, and Middle East and Africa, where North America currently dominates the global market.

Some of the major players in the global generative AI market include Adobe Inc., Amazon Web Services Inc., D-ID, Google LLC, MOSTLY AI Inc., OpenAI,, Synthesia, etc.

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Generative AI Market Report by Offering Type (Image, Video, Speech, and Others), Technology Type (Autoencoders, Generative Adversarial Networks, and Others), Application (Healthcare, Generative Intelligence, Media and Entertainment, and Others) and Region 2024-2032
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